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Page 4


www.us-tech.com


March, 2020 Tech-Op-ed SOUNDING OFF


By Michael Skinner Editor


Mirror, Mirror in the Walls: Digital Twins


C


onceptualized in David Gelernter’s book Mirror Worlds, in 1991, digital twins promise to optimize manufacturing in ways that, until now, have been impossible. Enabled by massive and recent increases in data stor-


age, computing power, networking, and sensor technology, a digital twin is a real-time digital copy of a physical system. The term “digital twin” is attributed to NASA’s John Vickers in a


roadmap report from 2010. He defines it in three distinct parts: the physical system, the digital model and the connections between the two. The connec- tions allow data to flow back and forth from the physical system, through sen- sors and networking, to the digital model, enabling it to respond and update. Industrial examples include wind turbines, locomotives, heavy equip-


ment, and other pieces of expensive machinery. For instance, General Electric uses a digital twin for collecting flight data from aircraft engines between London and Paris. The system uses this information to find defects or faults during the flight. This way if it requires maintenance or replacement, the part can be ready on the ground when the plane lands. Digital twins gather data about a machine’s well-being from thousands of


sensors, compiling the information into a readable or viewable model and sending it to the person or system in charge. Data is then used for predictive maintenance, optimization, simulation, and troubleshooting. What’s interesting about this type of simulation, is that the data does not


have to be centralized in one particular software program or environment. It can be spread across as many types and formats of data as the user is able to handle. A successful digital twin must provide a virtual mirror image of every process and event in its domain and do so in real time. In manufacturing, this digital map of machines and processes is used to


optimize production, from system layout to design and manufacturing of prod- uct. Investor and IT industry observer George Gilbert has identified the digi- tal twin as the tool to create what he calls the “AI-ssembly line.” At one point, machines had to be grouped around steam engines for power. Then came elec- tricity, and systems could be distributed in other more logical ways with pow- er flowing to them. Now, a company’s main resource is becoming its data, which is stored in


“data warehouses” or “data lakes.” This virtual ledger of operations, transac- tions, and products is a part of the digital model and flows between the phys- ical systems and the simulation. A huge advantage of digital twins is their ability to test new scenarios at


rates that are impossible for physical systems. Factories can quickly optimize line position, material flow, production speed and volume, and more, from a PC, as long as the sensors installed are generating accurate data. Digital twins are also disrupting traditional product lifecycle manage-


ment (PLM). PLM is expensive, time-consuming and must be extremely well- organized to be very beneficial. However, a digital twin makes the entire process transparent, significantly less expensive and is not nearly the same burden on a firm’s time and money. With a digital twin of a product, its entire lifecycle, from materials to manufacturing, transportation, use and disposal over any given time can be simulated, then tracked in real time and filed. Over successive generations, trends can be identified and the product opti- mized further. With the rise of cloud computing services and a movement toward IoT,


digital twins may take considerably less investment to develop, allowing smaller or niche companies to benefit. But, this will require more participa- tion in fields like machine learning, software engineering and AI. One problem with AI development, according to the late Marvin Minsky,


is that AI is fundamentally limited in its interaction with the physical world. AI combined with a digital twin, however, could create the right kind of feed- back loop, allowing the entire system to learn. In these applications, simula- tion may be as valuable as reality. r


PUBLISHER’S NOTE


By Jacob Fattal Publisher


Cloudy with a Chance of Carbon


ered by coal-burning electric plants are being proven wrong. In fact, according to a recent study, data centers owned by Google, Microsoft, Amazon, Face- book, and others have become hyper efficient. For example, Google’s data centers have reportedly gained seven times


W


their computing power over the last five years, without using any more elec- tricity. Gartner estimates that Google has more than 2.5 million servers and overall trend is toward “green” cloud computing. By 2017, Google had swapped all of its data centers over to use renewable power. The company now claims that all data it processes has “zero net carbon emissions.” Microsoft, for its part, has been focusing its efforts to “make the data cen-


ter disappear,” and to eliminate the impact of server farms on the environ- ment. Since 2012, the company has been carbon neutral, and has run com- pletely on renewable energy since 2014. Google and Microsoft accomplish this by leveraging renewable energy credits (RECs). An REC is a certificate that the purchaser is using energy that has only been generated from a renewable source. This way, the companies can say that their data centers run entirely on renewable energy, despite them being connected to the grid. Google has stated that it is “the largest corporate buyer of renewable en-


ergy in the world.” On the efficiency front, the company also uses machine learning algorithms to optimize its data centers. Every five minutes, Google’s system checks weather conditions and adjusts the temperature of its facilities automatically, saving significant energy. Amazon is still the largest provider of cloud computing services. Amazon


Web Services raked in nearly $26 billion in 2018 and owns over a third of the market.The company is traditionally tight-lipped about its carbon footprint statistics and has faced criticism. The winds are changing, though, and for the first time this year, Amazon released data about its global carbon footprint. Facing resistance from investors and critiques from organizations like


Greenpeace, Amazon is realizing that the way forward requires more trans- parency and a focus on environmental con- cerns. The company has pledged to achieve net zero carbon emissions by 2040. The digital cloud has a silver lining. r


ith a market value of over a quarter of a trillion dollars, cloud com- puting services have taken the world by storm. However, dire predic- tions of massive pollution arising from crammed data centers pow-


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